{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T20:30:59Z","timestamp":1774038659843,"version":"3.50.1"},"reference-count":55,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2023,4,6]],"date-time":"2023-04-06T00:00:00Z","timestamp":1680739200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["P01\u2010CA059827"],"award-info":[{"award-number":["P01\u2010CA059827"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01\u2010CA233487"],"award-info":[{"award-number":["R01\u2010CA233487"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2023,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Stereotactic body radiation therapy (SBRT) produces excellent local control for patients with hepatocellular carcinoma (HCC). However, the risk of toxicity for normal liver tissue is still a limiting factor. Normal tissue complication probability (NTCP) models have been proposed to estimate the toxicity with the assumption of uniform liver function distribution, which is not optimal. With more accurate regional liver functional imaging available for individual patient, we can improve the estimation and be more patient\u2010specific.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>To develop normal tissue complication probability (NTCP) models using pre\u2010\/during\u2010treatment (RT) dynamic Gadoxetic Acid\u2010enhanced (DGAE) MRI for adaptation of RT in a patient\u2010specific manner in hepatocellular cancer (HCC) patients who receive SBRT.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>24 of 146 HCC patients who received SBRT underwent DGAE MRI. Physical doses were converted into EQD2 for analysis. Voxel\u2010by\u2010voxel quantification of the contrast uptake rate (k1) from DGAE\u2010MRI was used to quantify liver function. A logistic dose\u2010response model was used to estimate the fraction of liver functional loss, and NTCP was estimated using the cumulative functional reserve model for changes in Child\u2010Pugh (C\u2010P) scores. Model parameters were calculated using maximum\u2010likelihood estimations. During\u2010RT liver functional maps were predicted from dose distributions and pre\u2010RT k1 maps with a conditional Wasserstein generative adversarial network (cWGAN). Imaging prediction quality was assessed using root\u2010mean\u2010square error (RMSE) and structural similarity (SSIM) metrics. The dose\u2010response and NTCP were fit on both original and cWGAN predicted images and compared using a Wilcoxon signed\u2010rank test.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Logistic dose response models for changes in k1 yielded D50 of 35.2 (95% CI: 26.7\u201347.5) Gy and k of 0.62 (0.49\u20130.75) for the whole population. The high baseline ALBI (poor liver function) subgroup showed a significantly smaller D50 of 11.7 (CI: 9.06\u201315.4) Gy and larger k of 0.96 (CI: 0.74\u20131.22) compared to a low baseline ALBI (good liver function) subgroup of 54.8 (CI: 38.3\u201379.1) Gy and 0.59 (CI: 0.48\u20130.74), with <jats:italic>p\u2010<\/jats:italic>values of\u00a0&lt;\u00a00.001 and\u00a0=\u00a00.008, respectively, which indicates higher radiosensitivity for the worse baseline liver function cohort. Subset analyses were also performed for high\/low baseline CP subgroups. The corresponding NTCP models showed good agreement for the fit parameters between cWGAN predicted and the ground\u2010truth during\u2010RT images with no statistical differences for low ALBI subgroup.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>NTCP models which incorporate voxel\u2010wise functional information from DGAE\u2010MRI k1 maps were successfully developed and feasibility was demonstrated in a small patient cohort. cWGAN predicted functional maps show promise for estimating localized patient\u2010specific response to RT and warrant further validation in a larger patient cohort.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.16386","type":"journal-article","created":{"date-parts":[[2023,3,29]],"date-time":"2023-03-29T14:54:34Z","timestamp":1680101674000},"page":"5597-5608","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Deep learning prediction of post\u2010SBRT liver function 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